Protein aggregation is frequently observed in neurodegenerative diseases, including the most common adult motor neuron disease, Amyotrophic Lateral Sclerosis (ALS). In familial ALS (FALS), 20% of patients inherit mutations in the dimeric enzyme Cu, Zn superoxide dismutase (SOD1) associated with increased formation of SOD1 aggregates that contribute to the cytotoxicity responsible for motor neuron cell death and underlying FALS. Our goal is to understand the mechanism of SOD1 aggregation. Accomplishing this goal may be a key step for the development of new FALS therapies, and will impact our understanding of over 60 additional aggregation-associated diseases. Our central hypothesis is that SOD1 aggregation is caused by the increased formation of unfolded/misfolded monomeric species, and/or defects in chaperone-mediated refolding. Specifically, we postulate that mutations (in case of FALS), fluctuations in cell environment and expression levels increase SOD1 dimer dissociation, loss of zinc, and/or the rate of formation of aggregates. We will therefore determine effects of FALS mutations, metals, on the mechanism of SOD1 aggregation. We will characterize the large-scale dynamics of a single SOD1 dimer in rapid computer simulations. We will assess the impact of FALS-associated mutations on SOD1 aggregation by examining the dynamics of mutant and wild type SOD1 molecules using novel multi-scale protein models for studies of large-scale protein conformational dynamics. We will also characterize the large-scale oligomerization dynamics of multiple SOD1 molecules in computer simulations of multiple SOD1 molecules and follow their oligomerization. We will assess the impact of FALS-associated mutations on SOD1 aggregation by examining the dynamics of mutant and wild type SOD1 molecules. For each step of aggregation reaction sequence we will experimentally determine rate and equilibrium constants using size exclusion chromatography, surface plasmon resonance, analytical ultracentrifugation, dynamic light scattering, electron microscopy, and computation. Results from experimental studies will be fed back to computational studies for validating and refining computational models. In turn, computational modeling will guide experimental work. RELEVANCE: Mechanistic understanding of SOD1 agggregation will provide a framework for understanding the origin and for developing treatments for this and other neurodegenerative diseases.